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Earnings forecasts and idiosyncratic volatilities

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  • Kryzanowski, Lawrence
  • Mohsni, Sana

Abstract

We test the theoretical relation between idiosyncratic return volatilities and the volatilities of cash-flow news based on the expected returns on equity (ROE) for CRSP stocks over the period 1977–2008. Consistent with economic intuition, we find that using analyst forecasts of earnings is superior to using realized earnings to proxy for market expectations about future cash flow news. Our findings are consistent with a market where stock return volatilities are positively and asymmetrically related to changes in the volatilities of expectations for a fundamental driver of cash flow news (ROE). Our findings are robust after correcting for forecast biases, various fundamental variables, newly-listed and mature firms, and periods with and without earnings announcements.

Suggested Citation

  • Kryzanowski, Lawrence & Mohsni, Sana, 2015. "Earnings forecasts and idiosyncratic volatilities," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 107-123.
    • Handle: RePEc:eee:finana:v:41:y:2015:i:c:p:107-123
    DOI: 10.1016/j.irfa.2015.06.001
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    More about this item

    Keywords

    Idiosyncratic volatilities; Earnings forecasts; I/B/E/S; Cash-flow news; Fundamental variables;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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